Lightweight Robust Framework for Workload Scheduling in Clouds

Muhammed Abdulazeez, Pawel Garncarek, Dariusz R. Kowalski, Prudence W.H. Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Reliability, security and stability of cloud services without sacrificing too much resources have become a desired feature in the area of workload management in clouds. The paper proposes and evaluates a lightweight framework for scheduling a workload which part could be unreliable. This unreliability could be caused by various types of failures or attacks. Our framework for robust workload scheduling efficiently combines classic fault-tolerant and security tools, such as packet/job scanning, with workload scheduling, and it does not use any heavy resource consuming tools, e.g., cryptography or non-linear optimization. More specifically, the framework uses a novel objective function to allocate jobs to servers and constantly decides which job to scan based on a formula associated with the objective function. We show how to set up the objective function and the corresponding scanning procedure to make the system provably stable, provided it satisfies a specific stability condition. As a result, we show that our framework assures cloud stability even if naive scanning-all and scanning-none strategies are not stable. We extend the framework to decentralized scheduling and evaluate it under several popular routing procedures.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 1st International Conference on Edge Computing, EDGE 2017
EditorsAndrzej M Goscinski, Min Luo
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages206-209
Number of pages4
ISBN (Electronic)9781538620175
DOIs
StatePublished - Sep 7 2017
Externally publishedYes
Event1st IEEE International Conference on Edge Computing, EDGE 2017 - Honolulu, United States
Duration: Jun 25 2017Jun 30 2017

Publication series

NameProceedings - 2017 IEEE 1st International Conference on Edge Computing, EDGE 2017

Conference

Conference1st IEEE International Conference on Edge Computing, EDGE 2017
CountryUnited States
CityHonolulu
Period6/25/176/30/17

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Abdulazeez, M., Garncarek, P., Kowalski, D. R., & Wong, P. W. H. (2017). Lightweight Robust Framework for Workload Scheduling in Clouds. In A. M. Goscinski, & M. Luo (Eds.), Proceedings - 2017 IEEE 1st International Conference on Edge Computing, EDGE 2017 (pp. 206-209). [8029277] (Proceedings - 2017 IEEE 1st International Conference on Edge Computing, EDGE 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEEE.EDGE.2017.36